Streaming a Kafka topic in a Delta table on S3 using Spark Structured Streaming
Our data strategy specifies that we should store data on S3 for further processing. Raw S3 data is not the best way of dealing with data on Spark, though. In this blog I’ll show how you can use Spark Structured Streaming to write JSON records of a Kafka topic into a Delta table.
Easy Spark optimization for max record: aggregate instead of join?
There is a lot of code that needs to make a selection based on a maximum value. One example are Kafka reads: we only want the latest offset for each key, because that’s the latest record. What is the fastest way of doing this?
Kafka, Spark and schema inference
At Wehkamp we use Apache Kafka in our event driven service architecture. It handles high loads of messages really well. We use Apache Spark to run analysis. From time to time, I need to read a Kafka topic into my Databricks notebook. In this article, I’ll show what I use to read from a Kafka topic that has no schema attached to it. We’ll also dive into how we can render the JSON schema in a human-readable format.
Simple Python code to send message to Slack channel (without packages)
Last week I was working on a Databricks script that needed to produce a Slack message as its final outcome. I lifted some code that used a Slack client that was PIP-installed. Unfortunately, I could not use the package on my cluster. Fortunately, the Slack API is so simple, that you don’t really need a package to post a simple message to a channel. In this blog I’ll show you the simplest way of producing awesome messages in Slack.
Validate strongly typed options when using config sections
I like to validate my application configuration upon startup. Especially when doing local development, I want to know which application settings are missing. I also like to know where I should add them. This blog shows how to implement validation of your configuration classes using data annotations.
Caching resized images on S3 with Databricks
When you are training a machine learning image classification model, you often need to resize the images your dataset into smaller ones. When you retrain your model on new data, you resize the images once more. In this blog I’ll share how S3 can be used to cache the resized images.
Sorting an array of a complex data type in Spark
Today we’ll be looking at sorting and reducing an array of a complex data type. I’m using Databricks to do Spark, but I’m sure the code is compatible. I’ll be using Spark SQL to show the steps. I’ve tried to keep the data as simple as possible. The example should apply to scenarios that are more complex.
Adding True/False and list value widgets to your Databricks notebook
As an engineer, I love to parametrise my applications. That’s why I love the widget-feature of Databricks notebooks, which allows me to do this with a nice UI. In this blog I’ll explore how to build a True/False widget and a list widget. I also show how to validate the values of required fields.
Investigate problems due to User-Agent using Bash
Last week we had some problems with the Google Ads bot. It was not able to crawl a bunch of URLs while the browser had no problem getting through. The only difference was the User-Agent. This send us on a debugging journey through Cloudflare, gateways and micro-sites. To assist us, we’ve created a small bash script to visit an URL and show some debug info.
Trigger Lambda for large S3 Bucket with SQS
At Wehkamp we use AWS Lambda to classify images on S3. The Lambda is triggered when a new image is uploaded to the S3 bucket. Currently we have over 6.400.000 images in the bucket. Now we would like to run the Lambda for all images of the bucket. In this blog I’ll show how we did this with a Python 3.6 script.